We explore on education factors that may have impacted minority language cultivation and usage using education statistic provided by World Bank(1). The data contains 3620 variables from year 1976 until 2100 (with some future projection population variables), but we limit our research to historical data up to 2016.
Due to the vast number of features, we first visualized the data in form of bitmap to identify if there’s any gaps (missing values) and to see how data are being structured. The data from World Bank is in stacked form, and the columns represent statistic for each year from 1976 onwards. We unstack the data enabling the variables represented in columns and added a new column named ‘year’. The data covers 242 countries, however we will filter and take only countries from language extinction data set.
fn<-createRasterBitmap(filterByYearUnstack(edstats))
We took a snapshot around the rows of 0.6 ratio which is about in the year 2000 and visualize the data again using interactive plot to estimate the variables that contains data.
edstats.2000<-filterByYearUnstack(edstats, 2000, 2000)
heatmap(edstats.2000)